Comparison of Signal‐ and Volume‐Based Ventilation‐Weighted Assessment Using 3D FLORET UTE MRI in Patients With Various Pulmonary Disease.

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Title: Comparison of Signal‐ and Volume‐Based Ventilation‐Weighted Assessment Using 3D FLORET UTE MRI in Patients With Various Pulmonary Disease.
Authors: Klimeš, Filip1,2,3 (AUTHOR), Plummer, Joseph W.4,5,6 (AUTHOR), Voskrebenzev, Andreas1,2,3 (AUTHOR), Gutberlet, Marcel1,2 (AUTHOR), Klein, Marius M.1,2 (AUTHOR), Willmering, Matthew M.4,7,8 (AUTHOR), Matheson, Alexander M.4 (AUTHOR), Bdaiwi, Abdullah S.4 (AUTHOR), Wacker, Frank1,2 (AUTHOR), Woods, Jason C.4,7,8,9 (AUTHOR), Cleveland, Zackary I.4,5,7,8 (AUTHOR), Walkup, Laura L.4,5,7,8 (AUTHOR), Vogel‐Claussen, Jens1,2,3 (AUTHOR) jens.vogel-clausen@charite.de
Source: Magnetic Resonance in Medicine. May2026, Vol. 95 Issue 5, p2814-2827. 14p.
Subjects: Ventilation monitoring, Magnetic resonance imaging, Respiration, Diagnostic imaging, Lung diseases
Abstract: Purpose: 3D free‐breathing, proton, contrast‐agent‐free MR methods are increasingly used for pulmonary ventilation‐weighted measurements. The methods are split between: (1) signal‐based, which rely on lung parenchyma signal changes during respiration, and (2) volume‐based that utilize the Jacobian determinant of deformation fields from the image registration. This study compares both proton methods using respiratory‐resolved images acquired using fermat‐looped orthogonally encoded trajectories (FLORET) acquisition. Methods: Free‐breathing FLORET data were acquired from participants with various pulmonary conditions (N = 29) and healthy controls (N = 7), and reconstructed into respiratory phase‐resolved images. Signal‐based regional ventilation (RVent) was quantified using the 3D phase‐resolved functional lung algorithm, and volume‐based Jacobian ventilation (JVent) was derived as the Jacobian of the deformation field from the direct image registration of the end‐expiratory image to the end‐inspiratory image. Differences between the means, coefficients of variation (CoVs), and their ventilation defect percent (VDP) were quantified by Bland–Altman plots. The spatial overlap of the defect maps was determined by multi‐class Sørensen–Dice coefficient, and Spearman correlations to 129Xe MRI were assessed. Results: In all study participants, statistically significant differences were found between means/CoVs of RVent and JVent parameters (both p < 0.0001), but not VDP (p = 0.38). The median spatial overlap of the defect maps was 86%. VDPRVent showed stronger correlation (ρ = 0.78, Meng Z = 4.36, p < 0.0001) to VDP129Xe than JVent (ρ = 0.34). Conclusion: Although both proton lung MRI methods successfully identified ventilation defects, the stronger correlation between signal‐based and 129Xe MRI indicates that RVent may provide a more reliable assessment of lung ventilation in clinical applications in comparison to volume‐based parameters. [ABSTRACT FROM AUTHOR]
Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Comparison of Signal‐ and Volume‐Based Ventilation‐Weighted Assessment Using 3D FLORET UTE MRI in Patients With Various Pulmonary Disease.
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  Data: &lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Ventilation+monitoring%22&quot;&gt;Ventilation monitoring&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Magnetic+resonance+imaging%22&quot;&gt;Magnetic resonance imaging&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Respiration%22&quot;&gt;Respiration&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Diagnostic+imaging%22&quot;&gt;Diagnostic imaging&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Lung+diseases%22&quot;&gt;Lung diseases&lt;/searchLink&gt;
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: 3D free‐breathing, proton, contrast‐agent‐free MR methods are increasingly used for pulmonary ventilation‐weighted measurements. The methods are split between: (1) signal‐based, which rely on lung parenchyma signal changes during respiration, and (2) volume‐based that utilize the Jacobian determinant of deformation fields from the image registration. This study compares both proton methods using respiratory‐resolved images acquired using fermat‐looped orthogonally encoded trajectories (FLORET) acquisition. Methods: Free‐breathing FLORET data were acquired from participants with various pulmonary conditions (N = 29) and healthy controls (N = 7), and reconstructed into respiratory phase‐resolved images. Signal‐based regional ventilation (RVent) was quantified using the 3D phase‐resolved functional lung algorithm, and volume‐based Jacobian ventilation (JVent) was derived as the Jacobian of the deformation field from the direct image registration of the end‐expiratory image to the end‐inspiratory image. Differences between the means, coefficients of variation (CoVs), and their ventilation defect percent (VDP) were quantified by Bland–Altman plots. The spatial overlap of the defect maps was determined by multi‐class S&#248;rensen–Dice coefficient, and Spearman correlations to 129Xe MRI were assessed. Results: In all study participants, statistically significant differences were found between means/CoVs of RVent and JVent parameters (both p &lt; 0.0001), but not VDP (p = 0.38). The median spatial overlap of the defect maps was 86%. VDPRVent showed stronger correlation (ρ = 0.78, Meng Z = 4.36, p &lt; 0.0001) to VDP129Xe than JVent (ρ = 0.34). Conclusion: Although both proton lung MRI methods successfully identified ventilation defects, the stronger correlation between signal‐based and 129Xe MRI indicates that RVent may provide a more reliable assessment of lung ventilation in clinical applications in comparison to volume‐based parameters. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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        Value: 10.1002/mrm.70239
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      – Code: eng
        Text: English
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        PageCount: 14
        StartPage: 2814
    Subjects:
      – SubjectFull: Ventilation monitoring
        Type: general
      – SubjectFull: Magnetic resonance imaging
        Type: general
      – SubjectFull: Respiration
        Type: general
      – SubjectFull: Diagnostic imaging
        Type: general
      – SubjectFull: Lung diseases
        Type: general
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      – TitleFull: Comparison of Signal‐ and Volume‐Based Ventilation‐Weighted Assessment Using 3D FLORET UTE MRI in Patients With Various Pulmonary Disease.
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            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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